There are several types of devices that are currently used in clinical settings for shade matching in dentistry. Spectrophotometers are considered to be amongst the most accurate and functional devices for these purposes. A spectrophotometer includes an optical radiation source, a light dispersing source, an optical measuring system, a detector, and a means of converting light to a signal for analysis and manipulation that is useful to the investigator. These devices measure an amount of light energy that is reflected from a specific object along the spectrum of visible light in 1-25 nm intervals. In the dental setting, the clinically obtained measurements are often compared to a shade guide to select a matching color of dental material that most closely matches a patient's natural tooth color.
Colorimeters are another device used for color measurement and shade matching. The data acquired by a colorimeter is often very precise because contact is made with the actual tooth. However, colorimeters do not measure spectral reflectance and are less accurate than spectrophotometers. Conventional colorimeters that utilize CIE recommended geometries for reflection measurements are generally not best for use of measuring objects with a translucent nature due to inaccuracies caused by the optical phenomenon of edge effects.
Yet another imaging device that is often used in clinical settings is the digital camera. Digital cameras are often used for this purpose because they are relatively inexpensive. Information obtained from a digital camera is generally input in a Red, Green and Blue (RGB) color space, but the RGB information is device dependent. As such, the RGB information must be adjusted and calibrated in order to utilize the color information extracted from a digital image. For color analysis involving digital camera sources, conversion equations from the RGB color space system to the CIE L*a*b* (CIELAB) color space are necessary. However, because RGB data obtained from a digital camera is device dependent, complex calibration models are needed in order to render with optimal accuracy.
For color analysis involving digital camera sources, conversion equations from RGB color space system to the CIELAB color space system may utilize a matrix that converts RGB color data to XYZ tristimulus values as follows:
      [                            X                                      Y                                      Z                      ]    =            [                                    0.412453                                0.357580                                0.180423                                                0.212671                                0.715160                                0.072169                                                0.019334                                0.119193                                0.950227                              ]        ×          [                                    R                                                G                                                B                              ]      
Prior work has evaluated four calibration models with three different digital cameras using the cameras' RGB values compared to the CIELAB values as a reference standard for accuracy measurements defined by ΔE. A second order polynomial regression (PRM2), a second order polynomial regression with eleven terms (PRM2-11), a third order polynomial regression (PRM3), and a model based on tetrahedral interpolation (TI) technique were all compared for accuracy. The models that were analyzed are as follows:
Second order polynomial regression (PRM2)L*=l0+l1R+l2G+l3B+l4RG+l5RB+l6GB+l7R2+l8G2+l9B2 
Second order polynomial regression with eleven terms (PRM2-11)L*=l0+l1R+l2G+l3B+l4RG+l5RB+l6GB+l7R2+l8G2+l9B2+l10RGB 
Third order polynomial regression (PRM3)L*=l0+l1R+l2G+l3B+l4RG+l5RB+l6GB+l7R2+l8G2+l9B2+l10RGB+l11R3+l12G3+l13B3+l14R2G+l15R2B+l16G2R+l17G2B+l18B2R+l10B2G 
In general, accuracy is improved by increasing the terms and raising the order of the regression model with proper terms being more important than increase of terms. In addition, using TI generally provided better results than using PRM2-11, and the results obtained using PRM3 were similar when compared to the results obtained using TI. Three out of 12 calibration/camera pairs were found to be below the ΔE acceptability limit of 2.1 lending to the idea that inexpensive digital cameras used in combination with specific calibration methods have potential in the clinical processes involving color replication.